An integrated genome and phenome-wide association study approach to understanding Alzheimer's disease predisposition

Background: Genome-wide association studies (GWAS) have identified common, heritable alleles that increase late-onset Alzheimer's disease (LOAD) risk. We recently published an analytic approach to integrate GWAS and phenome-wide association study (PheWAS) data, enabling identification of candidate traits and trait-associated variants impacting disease risk, and apply it here to LOAD. Methods: PheWAS was performed for 23 known LOAD-associated single nucleotide polymorphisms (SNPs) and 4:1 matched control SNPs using UK Biobank data. Traits enriched for association with LOAD SNPs were ascertained and used to identify trait-associated candidate SNPs to be tested for association with LOAD risk (17,008 cases; 37,154 controls). Results: LOAD-associated SNPs were significantly enriched for associations with 6/778 queried traits, including three platelet traits. The strongest enrichment was for platelet distribution width (PDW) (P=1.2x10-5), but no consistent direction of effect was observed between increased PDW and LOAD susceptibility across variants or in Mendelian randomization analysis. Of 384 PDW-associated SNPs identified by prior GWAS, 36 were nominally associated with LOAD risk and 5 survived false-discovery rate correction for multiple testing. Associations confirmed known LOAD risk loci near PICALM, CD2AP, SPI1, and NDUFAF6, and identified a novel risk locus in the epidermal growth factor receptor (EGFR) gene. Conclusions: Through integration of GWAS and PheWAS data, we identify substantial pleiotropy between genetic determinants of LOAD and of platelet morphology, and for the first time implicate EGFR - a mediator of Beta amyloid toxicity - in Alzheimer's disease susceptibility.

Efficacy and Safety of VNS Therapy or Continued Medication Management for Treatment of Adults with Drug-Resistant Epilepsy: Systematic Review and Meta-Analysis

Vagus nerve stimulation (VNS) Therapy® is an adjunctive neurostimulation treatment for people withdrug-resistant epilepsy (DRE) who are unwilling to undergo resective surgery, have had unsuccessfulsurgery or are unsuitable for surgery. A systematic review and meta-analysis were conducted todetermine the treatment effects of VNS Therapy as an adjunct to anti-seizure medications (ASMs) forthe management of adults with DRE.A literature search was performed in August 2020 of the Medline®, Medline® Epub Ahead of Print,Embase, and the Cochrane library databases. Outcomes examined included reduction in seizurefrequency, seizure freedom, ASM load, discontinuations, and serious adverse events (SAEs).Comparators included best medical practice, ASMs, low-stimulation or sham VNS Therapy.Four RCTs and six comparative observational studies were identified for inclusion. Against comparators,individuals treated with VNS had a significantly better odds of experiencing a ≥50% reduction in seizurefrequency (OR: 2.27 [95% CI: 1.47, 3.51]; p=0.0002), a ≥75% reduction in seizure frequency (OR: 3.56[95% CI: 1.59, 7.98]; p=0.002) and a reduced risk for increased ASM load (risk ratio: 0.36 [95% CI: 0.21,0.62]; p=0.0002). There was no difference in the odds of discontinuation or the rate of SAEs betweenVNS versus comparators.This meta-analysis demonstrated the benefits of VNS Therapy in people with DRE, which includedimprovement in seizure frequency without an increase in the rate of SAEs or discontinuations, therebysupporting the consideration of VNS Therapy for people who are not responding to ASMs and thoseunsuitable or unwilling to undergo surgery.

Efficacy and Safety of VNS Therapy or Continued Medication Management for Treatment of Adults with Drug-Resistant Epilepsy: Systematic Review and Meta-Analysis

Vagus nerve stimulation (VNS) Therapy® is an adjunctive neurostimulation treatment for people withdrug-resistant epilepsy (DRE) who are unwilling to undergo resective surgery, have had unsuccessfulsurgery or are unsuitable for surgery. A systematic review and meta-analysis were conducted todetermine the treatment effects of VNS Therapy as an adjunct to anti-seizure medications (ASMs) forthe management of adults with DRE.A literature search was performed in August 2020 of the Medline®, Medline® Epub Ahead of Print,Embase, and the Cochrane library databases. Outcomes examined included reduction in seizurefrequency, seizure freedom, ASM load, discontinuations, and serious adverse events (SAEs).Comparators included best medical practice, ASMs, low-stimulation or sham VNS Therapy.Four RCTs and six comparative observational studies were identified for inclusion. Against comparators,individuals treated with VNS had a significantly better odds of experiencing a ≥50% reduction in seizurefrequency (OR: 2.27 [95% CI: 1.47, 3.51]; p=0.0002), a ≥75% reduction in seizure frequency (OR: 3.56[95% CI: 1.59, 7.98]; p=0.002) and a reduced risk for increased ASM load (risk ratio: 0.36 [95% CI: 0.21,0.62]; p=0.0002). There was no difference in the odds of discontinuation or the rate of SAEs betweenVNS versus comparators.This meta-analysis demonstrated the benefits of VNS Therapy in people with DRE, which includedimprovement in seizure frequency without an increase in the rate of SAEs or discontinuations, therebysupporting the consideration of VNS Therapy for people who are not responding to ASMs and thoseunsuitable or unwilling to undergo surgery.

The Association between TREM2 Gene and Late-Onset Alzheimer’s Disease in Chinese Han Population

Objective: : The objective of this study was to evaluate the impact of single nucleotide polymorphisms (SNPs) in triggering receptor expressed on the myeloid cells 2 protein (TREM2) gene and their interaction with environmental factors and haplotypes on late-onset Alzheimer’s disease (LOAD). Methods: DNA was extracted from the whole blood of the participants and genotyped using PCR and followed by restriction fragment length polymorphism. The Hardy-Weinberg equilibrium test was used in the control group. Multivariate logistic regression analysis was used to determine the relationship between the 4 SNPs of the TREM2 gene and the risk of LOAD. Generalized multifactor dimensionality reduction was used to test the best interaction combination between SNPs and environmental factors. Results: Logistic regression analysis showed that the T allele of rs75932628 and the T allele of rs2234253 were independently associated with increased risk of LOAD, and adjusted odds ratios (ORs) were 1.81 (1.271–2.35) and 1.59 (1.15–2.03), respectively. However, there was no significant association with LOAD for rs142232675 and rs143332484. We found a best model significantly associated with LOAD risk that consisted of rs75932628 and smoking, which scored 10/10 for both the sign test and cross-validation consistency (p = 0.012). Stratified analysis indicated that current smokers with rs75932628-CT/TT genotype have the highest LOAD risk compared to never smokers with rs75932628 – CC genotype, OR (95% confidence interval) = 2.73 (1.72–3.79). Haplotypes of rs75932628 and rs2234253 were analyzed using the SHEsis online software. However, no haplotype was found to be significantly associated with the risk of LOAD. Conclusions: The T allele of rs75932628 and the T allele of rs2234253 and interaction between rs75932628 and smoking were all correlated with increased risk of LOAD.

Genetic variants shared between Alzheimer's disease and Parkinson's disease have been discovered in blood and brain samples. Somatic mosaicism might function as an accelerator

Alzheimer's disease and Parkinson's disease are the most prevalent aging-related neurodegenerative disorders. Controversy continues over amyotrophic lateral sclerosis being classified as an aging-dependent neurodegenerative disease. Systems biology techniques are required to parse and integrate models to provide insights into the link between genetic features and phenotypes. The H2 MAPT haplotype, which codes for the microtubule-associated protein tau, has been related to LOAD risk. New research is now examining postzygotic variation in post-mortem variation in brain tissues of AD patients. The genome has been found to have 50% of the autosomal recessive parkinsonism patients with EO Parkinsonism and sensorimotor polyneuropathy. The gene for this gene, Park7, also known as DJ1, is the third gene involved with EOPD. It is the most frequent genetic risk factor for PD. This whole-genome sequencing had a 50-coding-exon deletion (from exon 17 to exon 66) in a patient with Eo Parkinsonism.

Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer′s disease brains

In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimer′s disease (LOAD) and translate the associations to causation. Toward that goal, we conducted ATAC-seq profiling using neuronal nuclear protein (NeuN) sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner. We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions (±100kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets. In conclusion, using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci. Furthermore, our results convey mechanistic insights into sex differences in LOAD risk and clinicopathology.

Shared Genetic Background Between Cerebrospinal Fluid Biomarkers and Risk for Alzheimer’s Disease: A Two-Sample Mendelian Randomization Study

Background: Whether the epidemiological association of amyloid-β (Aβ) and tau pathology in late-onset Alzheimer’s disease (LOAD) is causal remains unclear. Objective: We aimed to investigate the shared genetic background between the cerebrospinal fluid (CSF) biomarkers for Aβ and tau pathology and the risk of LOAD. Methods: We conducted a two-sample Mendelian randomization (MR) analysis. We used summary statistics of genome-wide association studies for CSF biomarkers (Aβ 1–42 [Aβ], phosphorylated tau181 [p-tau], and total tau [t-tau]) in 3,146 individuals and for LOAD in 21,982 cases and 41,944 controls. We tested the association between changes in the genetically predicted CSF biomarkers and LOAD risk. Results: We found a decrease in LOAD risk per one-standard-deviation (SD) increase in the genetically predicted CSF Aβ (odds ratio [OR], 2.87×10–3 for AD; 95%confidence interval [CI], 1.54×10–4 –0.05; p = 8.91×10–5). Conversely, we observed an increase in LOAD risk per one-SD increase in the genetically predicted CSF p-tau (OR, 19.46; 95%CI, 1.50–2.52×102; p = 0.02) and t-tau (OR, 33.80; 95%CI, 1.57–7.29×102; p = 0.02). However, only the association between p-tau and the risk for LOAD remained significant after the exclusion of the APOE variant (rs769449). Conclusion: We found the causal association between CSF biomarkers and the risk for LOAD. Our results suggest that the etiology of LOAD involves multiple biological processes, including the pathways of Aβ and tau proteins. Further MR studies using large-scale data of multiple candidate biomarkers are needed to elucidate the pathophysiology of LOAD.

Examination of the Effect of Rare Variants in TREM2, ABI3, and PLCG2 in LOAD Through Multiple Phenotypes

Background: Rare variants in PLCG2 (p.P522R), ABI3 (p.S209F), and TREM2 (p.R47H, p.R62H) have been associated with late onset Alzheimer’s disease (LOAD) risk in Caucasians. After the initial report, several studies have found positive results in cohorts of different ethnic background and with different phenotype. Objective: In this study, we aim to evaluate the association of rare coding variants in PLCG2, ABI3, and TREM2 with LOAD risk and their effect at different time points of the disease. Methods: We used a European American cohort to assess the association of the variants prior onset (using CSF Aβ42, tau, and pTau levels, and amyloid imaging as endophenotypes) and after onset (measured as rate of memory decline). Results: We confirm the association with LOAD risk of TREM2 p.R47H, p.R62H and ABI3 p.S209F variants, and the protective effect of PLCG2 p.P522R. In addition, ABI3 and TREM2 gene-sets showed significant association with LOAD risk. TREM2 p.R47H and PLCG2 p.P522R variants were also statistically associated with increase of amyloid imaging and AD progression, respectively. We did not observe any association of ABI3 p.S209F with any of the other AD endophenotypes. Conclusion: The results of this study highlight the importance of including biomarkers and alternative phenotypes to better understand the role of novel candidate genes with the disease.

Rearing and handling injuries in broiler chickens and risk factors for wing injuries during loading

Some injuries to broilers occur during rearing, but most injuries occur during handling before slaughter. Records provided by a processing plant for loads transported over a 19 mo period during 2009 and 2010 were examined. The median percentage of wing injuries per load was 5.7%, whereas injuries to the legs, breast, or shoulders were all less than 1% per load. Risk factors for wing injuries were examined by considering the data from each load by handling event (i.e., loads originating from the same producer on the same date). A multilevel model with three levels, producer (n = 86), handling event (n = 1694), and load (n = 4219), was fitted. The final model included weight, sex, season, catching team, time of day at which loading began, speed of loading, and an interaction between speed of loading and time of day. Factors that reduced the risk of wing injuries were loading lighter birds, loads containing only cockerels, and loading in the fall. The predicted percentage of wing injuries was relatively constant for slower loading speeds, but it was increased significantly when faster loading speeds were adopted during daytime (0700–1700). Identification of these risk factors can be used to adjust loading practices.

Shared genetic background between cerebrospinal fluid biomarkers and risk for Alzheimer’s disease: A two-sample Mendelian randomisation study

Background: Whether the epidemiological association of amyloid beta (Aβ) and tau pathology with Alzheimer’s disease (AD) is causal remains unclear. Recent failures to demonstrate the efficacy of several Aβ-modifying drugs may indicate a possibility that the observed association is not causal, which led to efforts to develop tau-directed treatments whose efficacy remains tentative. Methods: Herein, we conducted a two-sample Mendelian randomisation analysis to investigate shared genetic background between cerebrospinal fluid (CSF) biomarkers for amyloid and tau pathology and risk for AD, and to find genetic evidence for causal association between these CSF biomarkers and risk for AD. We used summary statistics of genome-wide association study (GWAS) for CSF biomarkers (Aβ 1-42 , phosphorylated tau 181 [p-tau], and total tau [t-tau]) in 3,146 individuals and for late-onset AD (LOAD) in 21,982 LOAD cases and 41,944 cognitively-normal controls. We tested association between changes in the genetically-predicted CSF biomarkers and LOAD risk. Results: We found a decrease in the LOAD risk per one-standard deviation (SD) increase in the genetically-predicted CSF Aβ (odds ratio [OR], 2.87×10 -3 for AD; 95% confidence interval [CI], 1.54×10 -4 –0.05; p = 8.91×10 -5 ). Conversely, we observed an increase in the LOAD risk per one-SD increase in the genetically-predicted CSF p-tau (OR, 19.46; 95% CI, 1.50–2.52×10 2 ; p = 0.02) and t-tau (OR, 33.80; 95% CI, 1.57–7.29×10 2 ; p = 0.02). Conclusions: Our findings suggest a shared genetic background between the CSF biomarkers and LOAD risk. Although it requires validation by future studies including more genetic variants identified in large-scale GWASs for CSF biomarkers, our results suggest a causal association between CSF biomarkers and risk for LOAD Keywords: CSF biomarkers, Amyloid, Tau, Alzheimer’s disease